We take security very seriously and work with Amazon Web Services and our credit card processor to assure its integrity in Cloud Leo:

Access to Cloud Leo resources is controlled. Access to Cloud Leo is gained through a custom license manager built specifically for you, using information provided at registration and secret keys you have with Amazon, to ensure that you and only those you authorize can use the service.

All data transmissions between the workbench and Cloud Leo are authenticated and encrypted. All transmissions of data between the workbench and Cloud Leo are authenticated via SSH and encrypted using 256-bit encryption.

Your data does not persist in Cloud Leo. All simulation data is purged from Cloud Leo instances provisioned for a simulation and the instances themselves are deleted once simulation results have been successfully downloaded back to the workbench for post-processing.

Your credit card information is handled by a PCI compliant card processor. No credit card data is stored on our web servers. All credit card information provided during registration is managed by our credit card processor, Stripe. Stripe is PCI compliant and certified as a Level 1 Service Provider, the most stringent level of certification available. Click here for more information about Stripe's security procedures.

The number of cloud instances is controlled by the max concurrent cpu usage setting. This can be changed by going into Window->Preferences->Run Preferences and changing the maximum concurrent cpu usage value.

It is important to note that the number of cpus per instance depends on the instance type used. If your instance type is cc1.4xlarge (which equates to 8 cpus), a value between 1 and 8 will boot 1 instance, a value between 9 and 16 will boot 2 instances, and a value between 17 and 24 will boot 3 instances, and so on.

It is not necessary to have enough cpus to run your case. If a smaller cluster is booted than needed, the additional LEO processes will time-share the cpus in your cluster. However, this will result in slower turnaround times.

Cloud Leo is ideal for independent consultants and small-medium sized design shops with the savvy to take full advantage of CFD but have been constrained from its use due to large upfront license fees, limited analysis capacity and infrastructure costs.

By using Cloud Leo, these individuals and organizations gain the ability to apply massive CFD capacity on-demand to carry out aero design quickly and cost effectively. They will be able to gain design robustness, agility and the means to differentiate themselves from the competition in the process.

At a solver level, Code Leo applies a number of techniques. Local time stepping is employed, as well as pre-conditioning with gauge pressure to speed up convergence for low speed flow problems. We also employ two convergence acceleration techniques: a residual propagation method for unstructured mesh, and a multi-grid scheme for structured mesh. For time accurate simulations that employ wall integration, we employ dual time stepping to facilitate convergence. Finally, for highly skewed meshes, our cell-vertex numerical scheme produces accurate results with fewer elements compared to cell-centered schemes. The need for fewer elements under this condition also results in improved turnaround time.

At an execution level, we support parallel execution over an MPICH2 ring, and meshes may be partitioned into O and H mesh components for even faster throughput.

At a hardware infrastructure level, we employ only the Amazon EC2 cluster compute instances, which currently include 8 and 16 core machines designed specifically to handle our class of engineering/scientific application. For more information about Amazon EC2 instance types click here.

Cloud Leo is accessed through a graphical workbench that you download to your local desktop/laptop. The workbench allows you to import section data, generate meshes and configure your simulation.

When you click on “Start Run”, the case files are uploaded securely to Cloud Leo, where one or more CFD analysis instances are dynamically provisioned on your behalf and initiated to carry out your simulation to completion. You’ll be able to monitor your cases from the workbench or simply walk away.

Upon completion, the output files from the simulation are downloaded securely back to the workbench for post-processing and analysis.

The ADS flow solver, Code Leo, is a fast and accurate solver for general flow configurations. It solves the Reynolds' Averaged Navier-Stokes equations numerically. Tempered by decades of cutting edge aerospace application, Code Leo is designed to cover a wide range of Mach numbers from 0.005 to 3.5, and accepts both structured and unstructured mesh as input to support a large class of flow problems.

Though Leo is a generalized flow solver, it is particularly adept at addressing turbomachinery-class problems. It is capable of handling anything from 2D cascade simulation on a desktop to large scale, multi-stage time accurate simulations across a cluster of high performance servers. Code Leo has been applied to a wide variety of axial and radial turbines and compressors, wind turbines and high performance jet engines.

Seeing is believing, so we've tried to make the process pretty easy for you. Check us out, register to our site to download an evaluation, and follow the installation procedure to request a 30 day evaluation license. If you like what you see, subscribe to use our products on a monthly basis and scale as your needs scale.

Here at ADS we've worked hard to impart the experiences we've gained designing commercial and military grade turbines and compressors. We think Code Wand is best in class--not because of fancy bells and whistles, but because Wand knows how to concentrate mesh nodes where they're needed most for your design needs.

We start by employing a dense OHH-type mesh topology to ensure the capture of flow phenomena near leading and trailing edges. This is coupled with an innovative clearance meshing algorithm that helps to improve the efficiency and performance of tip clearance and stator end gap meshes.

While we provide presets, you can precisely control the placement of mesh nodes across the flow field.

We apply a number of techniques to achieve fast turnaround time. Local time stepping is employed, as well as pre-conditioning with gauge pressure to speed up convergence for low speed flow problems. We also employ two convergence acceleration techniques: a residual propagation method for unstructured mesh, and a multi-grid scheme for structured mesh. For time accurate simulations that employ wall integration, we employ dual time stepping to facilitate convergence.

Code Leo employs cell vertex-based finite volume approximation to solve the governing equations. The cell-vertex approach has proven to be more accurate for stretched/skewed grids and is 4-6 times more memory efficient than comparable cell-centered techniques.

In addition, Leo employs a proprietary distribution formula to ensure the proper propagation of convection and pressure waves. In contrast to cell-centered schemes, our approach does not require 4th order smoothing as a necessity to achieve solution convergence. This results in a procedure we feel to be more physics-based in nature and more likely to deliver quality results.

Overall, the numerical procedure is second order accurate in space and time, even for highly skewed meshes.This is a real advantage over cell-centered approaches which require meshes that are second order accurate in space.

Code Wand does not support the meshing of non-axisymmetric casing treatments. A third party mesh converted into the restart file format employed by Cloud Leo may be used instead for analysis. Please contact technical support for more information.

Code Wand does not support the meshing of non-axisymmetric components such as volutes. A third party mesh converted into the restart file format employed by Cloud Leo may be used instead for analysis. Please contact technical support for more information.

Yes, Code Wand can support fillet meshing on pressure or suction side at the hub or tip. We support constant or variable radius fillets, and we support variable radius fillets with cutoff trailing edges, which is useful for radial impellers.

OHH mesh for viscous flow analysis with two types of clearance meshing

OH mesh for viscous flow analysis with two types of clearance meshing

Hybrid H mesh for inviscid and viscous analysis

Sheared H mesh for inviscid flow analysis

Though we support several mesh topologies, we strongly recommend using an OHH mesh topology with Type 2 clearance meshing. This topology surrounds the airfoil with an O-mesh and places H-meshes on the pressure and suction sides of the airfoil as well as at the leading and trailing edges in order to improve resolution of wake capture. Our innovative tip clearance meshing approach provides both excellent resolution and high efficiency, resulting in a 30% improvement in turnaround time vs. traditional approaches.